Background: The deployment of autonomous vehicles (AVs) has foregrounded a dense intersection of ethical decision-making, regulatory design, liability distribution, and algorithmic transparency. Existing scholarship highlights normative dilemmas (trolley-like trade-offs), heterogeneous societal preferences, and emergent legal ambiguities that together complicate responsible AV rollout (Bonnefon et al., 2016; Awad et al., 2018; Kriebitz et al., 2022).

Objective: This article synthesizes ethical theory, empirical findings on moral preferences, regulatory responses, and technical approaches to AV decision-making to propose an integrated framework—an ethical trajectory and liability architecture—that supports accountable AV behavior while remaining sensitive to plural moral perspectives and evolving technological constraints.

 Methods: The study conducts an integrative conceptual analysis grounded strictly in the supplied literature. It combines normative ethical analysis, comparative interpretation of empirical moral-choice studies, and a technical review of ethical trajectory planning, localization and sensing, and simulation frameworks. The approach is methodical: (1) map moral problems identified in empirical and philosophical literature; (2) derive design principles for AV control systems and ethics modules; (3) analyze legal and liability frameworks; (4) propose a governance architecture aligning ethics-by-design with legal accountability. Each step is substantiated with cited findings and theoretical elaboration.

 Results: The synthesis reveals three interdependent domains that must be aligned: (A) an ethics-of-risk orientation in system behavior rather than sole reliance on trolley-problem solutions (Geisslinger et al., 2021; Geisslinger et al., 2023); (B) a layered liability model distributing responsibility across manufacturers, software suppliers, and operators in accordance with foreseeability and control (Marchant & Lindor, 2012; Douma & Palodichuk, 2012; Xiao & Cao, 2017); (C) technical design patterns that operationalize fairness, transparency, and risk-sensitive planning through ethical trajectory planners, advanced localization, and sensor simulation-informed validation (Geisslinger et al., 2023; Kuutti et al., 2018; Elmquist et al., 2021).

Conclusions: Rather than seeking a single universal moral algorithm, effective governance of AVs requires integrated socio-technical architectures that explicitly trade off risks, embed normative pluralism into configurable policy layers, and align incentives via liability reforms. The proposed ethical trajectory and liability architecture offers a practical pathway for policymakers, designers, and legal actors to operationalize ethical values while safeguarding public trust and innovation. Future work must translate these conceptual prescriptions into empirical validation, juridical pilots, and participatory governance experiments. (Max ~400 words)